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DOI: 10.14569/IJACSA.2019.0100567
PDF

Fast and Efficient In-Memory Big Data Processing

Author 1: Babur Hayat Malik
Author 2: Maliha Maryam
Author 3: Myda Khalid
Author 4: Javaria Khlaid
Author 5: Najam Ur Rehman
Author 6: Syeda Iqra Sajjad
Author 7: Tanveer Islam
Author 8: Umair Ahmed Butt
Author 9: Ali Raza
Author 10: M. Saad Nasr

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 10 Issue 5, 2019.

  • Abstract and Keywords
  • How to Cite this Article
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Abstract: With the passage of time, the data is growing exponentially and the mostly endured areas are social media networks, media hosting applications, and servers. They have thousands of Tera-bytes of data and the efficient systems, however, they are as yet confronting issue to oversee such volume of information and its size is growing each day. Data systems retrieve information with less time of In-memory. Instead of each factor data systems are required to define good usage of cache and fast memory access with help of optimization. The proposed technique to solve this problem can be the optimal indexing technique with better and efficient utilization of Cache and having less overhead of DRAM with the goal that energy can also be saved for the high-end servers.

Keywords: Big data processing; indexing techniques; R-tree; B-tree; X-tree; hashing; inverted index; graph query tree

Babur Hayat Malik, Maliha Maryam, Myda Khalid, Javaria Khlaid, Najam Ur Rehman, Syeda Iqra Sajjad, Tanveer Islam, Umair Ahmed Butt, Ali Raza and M. Saad Nasr, “Fast and Efficient In-Memory Big Data Processing” International Journal of Advanced Computer Science and Applications(IJACSA), 10(5), 2019. http://dx.doi.org/10.14569/IJACSA.2019.0100567

@article{Malik2019,
title = {Fast and Efficient In-Memory Big Data Processing},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2019.0100567},
url = {http://dx.doi.org/10.14569/IJACSA.2019.0100567},
year = {2019},
publisher = {The Science and Information Organization},
volume = {10},
number = {5},
author = {Babur Hayat Malik and Maliha Maryam and Myda Khalid and Javaria Khlaid and Najam Ur Rehman and Syeda Iqra Sajjad and Tanveer Islam and Umair Ahmed Butt and Ali Raza and M. Saad Nasr}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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